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Computer Science Grad Jobs in Houston, TX (NOW HIRING)

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Computer Science Grad information

What is a computer science grad?

Computer Science grads are individuals who have completed a degree program in computer science, typically at the undergraduate or graduate level. They possess knowledge and skills in areas such as programming, algorithms, data structures, software engineering, and computer systems. These graduates are equipped to pursue careers in various tech fields including software development, data analysis, cybersecurity, and more. Their education often includes both theoretical foundations and practical experience with modern technologies.

What are some common entry-level positions for recent computer science grads, and how do they typically collaborate within a team?

Recent computer science graduates often start in roles such as software engineer, QA analyst, IT support specialist, or junior web developer. In these positions, you'll usually work as part of a project team alongside more experienced engineers, designers, and sometimes product managers. Collaboration is key—you'll participate in code reviews, daily stand-up meetings, and pair programming sessions to learn best practices and contribute to shared goals. This team-oriented environment not only helps build technical skills but also offers mentorship opportunities and exposure to different aspects of software development.

What are the key skills and qualifications needed to thrive as a computer science grad, and why are they important?

To thrive as a Computer Science Graduate, you need a solid understanding of programming languages, algorithms, data structures, and fundamental computer science concepts, typically gained through a bachelor's degree in computer science or a related field. Familiarity with development environments, version control systems like Git, and frameworks relevant to your specialization is often expected. Problem-solving, teamwork, and strong communication skills help you collaborate efficiently and adapt to evolving project requirements. These skills and qualities are crucial for building robust software solutions and succeeding in dynamic technology-driven workplaces.

What is the difference between Computer Science Grad vs Software Developer?

AspectComputer Science GradSoftware Developer
CredentialsDegree in Computer Science or related fieldOften requires a degree, but certifications and experience can suffice
Work EnvironmentAcademic settings, internships, entry-level rolesCorporate offices, tech companies, startups
Industry UsageEducational institutions, entry-level tech rolesProduct development, application building, coding tasks
Search & Comparison IntentEntry-level, educational background, career startPractical coding, project work, job opportunities

While a Computer Science Grad typically refers to someone with a degree in computer science, a Software Developer is a professional actively involved in coding and building software applications. Many Computer Science Grads pursue roles as Software Developers, but the latter emphasizes practical skills and work experience. Understanding this difference helps job seekers target the right roles and employers effectively.

What are popular job titles related to Computer Science Grad jobs in Houston, TX?

For Computer Science Grad jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Computer Science Grad jobs in Houston, TX look for?

The top searched job categories for Computer Science Grad jobs in Houston, TX are:

What cities near Houston, TX are hiring for Computer Science Grad jobs?

Cities near Houston, TX with the most Computer Science Grad job openings:

Computer Science Grad jobs near you
Infographic showing various Computer Science Grad job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 79% Physical, 2% Hybrid, and 19% Remote job distribution.

Algorithm Engineer, Deep Learning & Vision (New Grad)

Houston, TX • On-site

Bot Auto
See more jobs at Bot Autoexternal

Full-time

Posted 28 days ago

Job description

Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
Key Responsibilities
  • Model Implementation & Iteration: Participate in the development, training, and optimization of state-of-the-art deep learning models for autonomous driving, with a focus on end-to-end architectures, including perception, online mapping, and end-to-end planning.
  • Full Lifecycle Execution: Engage in the entire machine learning workflow under the guidance of domain experts, spanning from data curation and data analysis to model experimentation, hyperparameter tuning, and rigorous performance metric verification.
  • Cross-Functional Collaboration: Partner with simulation, infrastructure, and downstream planning/control teams to deploy, evaluate, and integrate machine learning components into our production pipeline for autonomous trucks.
  • Literature Tracking: Stay abreast of the latest research breakthroughs in computer vision and generative AI, and actively bench-test promising SOTA methods to solve real-world corner cases.
How You'll Grow
This matters as much to us as what you'll ship.
  • You get a real mentor. Every engineer is paired with senior-level engineers developing you. Mentorship here is weighted toward design and judgment: how to frame a problem, what to build and why, how to tell whether a solution is actually right.
  • We promote fast. Managers are expected to push engineers to attempt work above their current level, and to promote in the next cycle when they deliver it.
Qualifications
Required:
  • Education: A Bachelor's, Master's, or Ph.D. (including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.
  • You have trained neural networks. Coursework, research, personal projects, open-source work, and internships all count. We care that you have actually run the loop: built a model, trained it, found out why it was not working, and fixed it.
  • Core Knowledge: Strong theoretical foundation in machine learning and deep learning, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs).
  • Technical Stack: Proficiency in Python and deep learning frameworks such as PyTorch, along with strong software engineering fundamentals (data structures, algorithms, and clean coding practices).
  • Attributes: High self-motivation, strong analytical and problem-solving skills, a fast learner in a high-velocity startup environment, and a strong team-player mindset.
Preferred:
  • Computer vision. Research or projects in computer vision, and particularly in 3D.
  • Specific Research Directions: Academic thesis or deeply focused research experience in one or more of the following domains:
    • Computer Vision (2D or 3D)
    • Online Mapping, Vectorization, or Visual SLAM
    • Prediction and Behavioral Modeling
  • Academic Achievements: A track record of research publications in machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS).
  • Engineering Plus: Hands-on experience with model deployment, quantization, distillation, or inference acceleration tools (e.g., TensorRT, ONNX, CUDA, C++).
  • Industry Exposure: Prior internship experience within the autonomous driving industry or advanced robotics labs.

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